Linear-scaling self-consistent implementation of the van der Waals density functional

An efficient linear-scaling approach to the van der Waals density functional in electronic-structure calculations is demonstrated. The nonlocal correlation potential needed in self-consistent calculations is derived in a practical form. This enables also an efficient determination of the Hellmann-Feynman forces on atoms. The numerical implementation employs adaptive quadrature grids in real space resulting in a fast and an accurate evaluation of the functional and the potential. The approach is incorporated in the atomic orbital code SIESTA. The application of the method to the S22 set of noncovalently bonded molecules and comparison with the quantum chemistry data reveal an overall agreement but show that different exchange functionals should be used for different types of bonds.Peer reviewe

Cyclic Density Functional Theory : A route to the first principles simulation of bending in nanostructures

We formulate and implement Cyclic Density Functional Theory (Cyclic DFT) -- a self-consistent first principles simulation method for nanostructures with cyclic symmetries. Using arguments based on Group Representation Theory, we rigorously demonstrate that the Kohn-Sham eigenvalue problem for such systems can be reduced to a fundamental domain (or cyclic unit cell) augmented with cyclic-Bloch boundary conditions. Analogously, the equations of electrostatics appearing in Kohn-Sham theory can be reduced to the fundamental domain augmented with cyclic boundary conditions. By making use of this symmetry cell reduction, we show that the electronic ground-state energy and the Hellmann-Feynman forces on the atoms can be calculated using quantities defined over the fundamental domain. We develop a symmetry-adapted finite-difference discretization scheme to obtain a fully functional numerical realization of the proposed approach. We verify that our formulation and implementation of Cyclic DFT is both accurate and efficient through selected examples. The connection of cyclic symmetries with uniform bending deformations provides an elegant route to the ab-initio study of bending in nanostructures using Cyclic DFT. As a demonstration of this capability, we simulate the uniform bending of a silicene nanoribbon and obtain its energy-curvature relationship from first principles. A self-consistent ab-initio simulation of this nature is unprecedented and well outside the scope of any other systematic first principles method in existence. Our simulations reveal that the bending stiffness of the silicene nanoribbon is intermediate between that of graphene and molybdenum disulphide. We describe several future avenues and applications of Cyclic DFT, including its extension to the study of non-uniform bending deformations and its possible use in the study of the nanoscale flexoelectric effect.Comment: Version 3 of the manuscript, Accepted for publication in Journal of the Mechanics and Physics of Solids, http://www.sciencedirect.com/science/article/pii/S002250961630368

KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory

Orbital-free density functional theory (OF-DFT) holds the promise to compute ground state molecular properties at minimal cost. However, it has been held back by our inability to compute the kinetic energy as a functional of the electron density only. We here set out to learn the kinetic energy functional from ground truth provided by the more expensive Kohn-Sham density functional theory. Such learning is confronted with two key challenges: Giving the model sufficient expressivity and spatial context while limiting the memory footprint to afford computations on a GPU; and creating a sufficiently broad distribution of training data to enable iterative density optimization even when starting from a poor initial guess. In response, we introduce KineticNet, an equivariant deep neural network architecture based on point convolutions adapted to the prediction of quantities on molecular quadrature grids. Important contributions include convolution filters with sufficient spatial resolution in the vicinity of the nuclear cusp, an atom-centric sparse but expressive architecture that relays information across multiple bond lengths; and a new strategy to generate varied training data by finding ground state densities in the face of perturbations by a random external potential. KineticNet achieves, for the first time, chemical accuracy of the learned functionals across input densities and geometries of tiny molecules. For two electron systems, we additionally demonstrate OF-DFT density optimization with chemical accuracy.Comment: 10 pages, 8 figure

Algorithmes incrémentaux pour la théorie de la fonctionnelle de la densité

The ability to model molecular systems on a computer has become a crucial tool for chemists. Indeed molecular simulations have helped to understand and predict properties of nanoscopic world, and during the last decades have had large impact on domains like biology, electronic or materials development. Particle simulation is a classical method of molecular dynamic. In particle simulation, molecules are split into atoms, their inter-atomic interactions are computed, and their time trajectories are derived step by step. Unfortunately, inter-atomic interactions computation costs prevent large systems to be modeled in a reasonable time. In this context, our research team looks for new accurate and efficient molecular simulation models. One of our team's focus is the search and elimination of useless calculus in dynamical simulations. Hence has been proposed a new adaptively restrained dynamical model in which the slowest particles movement is frozen, computational time is saved if the interaction calculus method do not compute again interactions between static atoms. The team also developed several interaction models that benefit from a restrained dynamical model, they often updates interactions incrementally using the previous time step results and the knowledge of which particle have moved.In the wake of our team's work, we propose in this thesis an incremental First-principles interaction models. Precisely, we have developed an incremental Orbital-Free Density Functional Theory method that benefits from an adaptively restrained dynamical model. The new OF-DFT model keeps computation in Real-Space, so can adaptively focus computations where they are necessary. The method is first proof-tested, then we show its ability to speed up computations when a majority of particle are static and with a restrained particle dynamic model. This work is a first step toward a combination of incremental First-principle interaction models and adaptively restrained particle dynamic models.In the wake of our team's work, we propose in this thesis an incremental First-principles interaction models. Precisely, we have developed an incremental Orbital-Free Density Functional Theory method that benefits from an adaptively restrained dynamical model. The new OF-DFT model keeps computation in Real-Space, so can adaptively focus computations where they are necessary. The method is first proof-tested, then we show its ability to speed up computations when a majority of particle are static and with a restrained particle dynamic model. This work is a first step toward a combination of incremental First-principle interaction models and adaptively restrained particle dynamic models.L'informatique est devenue un outil incontournable de la chimie. En effet la capacité de simuler des molécules sur ordinateur a aidé à la compréhension du monde nanoscopic et à la prédiction de ses propriétés. La simulation moléculaire a eu ces dernières décennies un impact scientifique énorme en biologie, en électronique, en science des matériaux ... La simulation de particules est une des méthodes classiques de dynamique moléculaire, les molécules y sont divisées en atomes, leurs interactions relatives calculées et leurs trajectoires déduites pas à pas. Malheureusement un calcul précis des interactions entre atomes demande énormément d'opérations et donc de temps, ce qui limite la portée de la simulation moléculaire à des systèmes de taille raisonnable. C'est dans ce contexte que notre équipe recherche de nouveaux modèles de simulation moléculaire rapide et précis. Un des angles de recherche est l'élimination des calculs inutiles des simulations. L'équipe a ainsi proposé un modèle de dynamique moléculaire dite restreinte de manière adaptative dans lequel le mouvement des particules les plus lentes est bloqué. Si la simulation ne recalcule pas les interactions inchangées entre atomes bloqués, le calcul des interactions est plus rapide. L'équipe a aussi développé plusieurs modèles d'interactions plus efficaces pour des modèles de dynamique restreinte de particules, ils mettent à jour les interactions de façon incrémentale en utilisant les résultats du pas de temps précédent et la liste des particules mobiles. Dans le sillage des travaux de notre équipe de recherche, nous proposons dans cette thèse une méthode incrémentale pour calculer des interactions interatomique basées sur les modèles de Théorie de la Fonctionnelle de la Densité Sans Orbitale. La nouvelle méthode garde les calculs dans l'espace réel et peut ainsi concentrer les calculs où cela est nécessaire. Dans ce manuscrit nous vérifions cette méthode, puis nous évaluons les gains de vitesse lorsqu'une majorité de particule est bloquée, avec un modèle de dynamique restreinte. Ces travaux sont un pas vers la l'intégration de modèles d'interactions Premier-principes pour des modèles dynamiques restreint de manière adaptative

Thermochemical evaluation of adaptive and fixed density functional theory quadrature schemes

A systematic study is made of the accuracy and efficiency of a number of existing quadrature schemes for molecular Kohn–Sham Density-Functional Theory (DFT) using 408 molecules and 254 chemical reactions. Included are the fixed SG-x (x = 0–3) grids of Gill et al., Dasgupta, and Herbert, the 3-zone grids of Treutler and Ahlrichs, a fixed five-zone grid implemented in Molpro, and a new adaptive grid scheme. While all methods provide a systematic reduction of errors upon extension of the grid sizes, significant differences are observed in the accuracies for similar grid sizes with various approaches. For the tests in this work, the SG-x fixed grids are less suitable to achieve high accuracies in the DFT integration, while our new adaptive grid performed best among the schemes studied in this work. The extra computational time to generate the adaptive grid scales linearly with molecular size and is negligible compared with the time needed for the self-consistent field iterations for large molecules. A comparison of the grid accuracies using various density functionals shows that meta-GGA functionals need larger integration grids than GGA functionals to reach the same degree of accuracy, confirming previous investigations of the numerical stability of meta-GGA functionals. On the other hand, the grid integration errors are almost independent of the basis set, and the basis set errors are mostly much larger than the errors caused by the numerical integrations, even when using the smallest grids tested in this wor

On 3-D inelastic analysis methods for hot section components (base program)

A 3-D Inelastic Analysis Method program is described. This program consists of a series of new computer codes embodying a progression of mathematical models (mechanics of materials, special finite element, boundary element) for streamlined analysis of: (1) combustor liners, (2) turbine blades, and (3) turbine vanes. These models address the effects of high temperatures and thermal/mechanical loadings on the local (stress/strain)and global (dynamics, buckling) structural behavior of the three selected components. Three computer codes, referred to as MOMM (Mechanics of Materials Model), MHOST (Marc-Hot Section Technology), and BEST (Boundary Element Stress Technology), have been developed and are briefly described in this report